The iris surrounds the dark, inner pupil region of an eye and extends concentrically to the white sclera of the eye.
A. K. Jain, A. Ross, and S. Prabhakar, “An introduction to biometric recognition,” IEEE Trans. Circuits Syst. Video Technol., vol. 14, 2004 discloses that the iris of the eye is a near-ideal biometric.
For the purposes of iris based recognition, an image of a subject comprising an iris region is acquired with an imaging system, typically using infra-red (IR) illumination to bring out the main features of an underlying iris pattern.
Then, eye and/or iris detection is applied over the whole acquired image to identify a region of the image containing the iris pattern. Iris segmentation is performed on the detected region of the image in order to define an iris segment, and then feature extraction is performed on the iris segment. The extracted features can be used to generate an iris code for the subject of the acquired image and this can be used in conjunction with stored iris code(s) to identify, recognise or authenticate the subject of the image.
If there are certain requirements for the input image regarding the iris size and location, as in the case of BS ISO/IEC 19794-6:2005 compliant images, this can speed up the detection process.
Without such requirements, there can be a large variation in iris size and location within acquired images. For example, in the context of handheld devices, for example, smartphones, the range of distances between the eye and the device can vary from less than 15 cm out to 40 cm or more, depending on how close a user holds the device or the length of the user's arm—this can affect the size, location and quality of the iris region appearing in an acquired image.
Thus, the detection process can be slow and possibly lead to false candidates, since the initial processing step has to detect where the iris is located within the whole acquired image and determine the size of the iris.
As indicated, in an attempt to speed up processing, some systems perform relatively large-scale and so faster, eye detection before performing refined iris detection on the result of the eye detection. However, this can result in non-segmented or wrongly segmented iris images, especially in cases where the image is so closely acquired that only a portion of the eye is included therein. In these cases, since the full eye is not within the image, the eye detection can fail to correctly locate the eye, thus providing a poor quality or wrong result for the following image processing.